A large annotated medical image dataset for the development and evaluation of segmentation algorithms

25 Feb 2019Amber L. SimpsonMichela AntonelliSpyridon BakasMichel BilelloKeyvan FarahaniBram van GinnekenAnnette Kopp-SchneiderBennett A. LandmanGeert LitjensBjoern MenzeOlaf RonnebergerRonald M. SummersPatrick BilicPatrick F. ChristRichard K. G. DoMarc GollubJennifer Golia-PernickaStephan H. HeckersWilliam R. JarnaginMaureen K. McHugoSandy NapelEugene VorontsovLena Maier-HeinM. Jorge Cardoso

Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is contingent on the availability of high-quality imaging data with corresponding labels provided by experts... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet